Greg is a computer scientist working at the Hydrologic Applied Innovations Lab (HAIL) based in the New York Water Science Center. He works primarily in Artificial Intelligence research and engineering for a variety of problem spaces in natural science.
Greg started his career with the USGS as an intern beginning the summer of 2014 while attending George Mason University for his Bachelor of Science in Computer Science. Working under the National Research Program, he performed research and developed software to assess Storm-Tide water levels and generate wave statistics using digital signal processing, statistics, and spectral analysis.
After completing his degree at GMU in May 2016, he joined the Office of Surface Water in the Water Mission Area (WMA) full-time continuing his previous work as well as working on software for streamflow prediction, stream statistics national scale geospatial analysis, and multibeam echosounder processing. In October 2017, he then joined the Geo-Intelligence Branch of the Integrated Modeling and Prediction Division in the WMA. His work focused on Rapid Flood Inundation Modeling, Open Geospatial Consortium APIs, and services for both databases and geospatial data servers.
In October 2020, he joined HAIL as an Artificial Intelligence Researcher and Engineer. He worked on a broad set of problem spaces including groundwater recharge forecasting, graph theory route optimization, species image segmentation and identification, unsteady streamflow prediction, and virtual reality flood inundation simulations.